System and method for adapting market data and evaluating unequal offers

ABSTRACT

A system includes at least one server that implements a metric server adapter and a metrics application. The metric server adapter includes governing logic that manages an evaluation service and predefined instructions and/or data used to provide the evaluation service. The metrics application executes the evaluation service in coordination with the metric server adapter. The server receives or retrieves price data sets, at least one of which represents an unequal offer. The metrics application obtains time-dependent metric data including market reference price data for one or more responsive items, dynamically discovers a difference in the attribute data, and defines offer-specific instructions for adapting the metric data. One or more adjustment values applied to the market reference price data transforms the market reference price data. A comparative metric comprising a differential ratio or index value compares the price data in the offer with the offer-specific market reference price data values.

BACKGROUND

Technical Field

This present disclosure generally relates to electronic commercesoftware applications and, more particularly, to evaluating prices andtransactions for purchasing.

Description of the Related Art

Commodity items such as lumber, agricultural products, metals, andlivestock/meat are usually traded in the open market between a number ofbuyers and sellers. The sales transactions of most commodity itemsinvolve a number of parameters. For instance, in the trade of commoditylumber, a buyer usually orders materials by specifying parameters suchas lumber species, grade, size (i.e., 2×4, 2×10, etc.), and length, aswell as the “tally” or mix of units of various lengths within theshipment, method of transportation (i.e., rail or truck), shipping terms(i.e., FOB or delivered), and desired date of receipt, with eachparameter influencing the value of the commodity purchase. Given themultiple possible combinations of factors, a commodity buyer often findsit difficult to objectively compare similar but unequal offerings amongcompeting vendors.

For example, in a case where a lumber buyer desires to order a railcarload of spruce (SPF) 2×4's of #2 & Better grade, the buyer would queryvendors offering matching species and grade carloads seeking the bestmatch for the buyer's need or tally preference at the lowest marketprice. Lumber carloads are quoted at a price per thousand board feet forall material on the railcar. When the quoted parameters are notidentical, it is very difficult for buyers to determine the comparativevalue of unequal offerings.

Typically, a lumber buyer will find multiple vendors each havingdifferent offerings available. For example, a railcar of SPF 2×4's maybe quoted at a rate of $300/MBF (thousand board feet) by multiplevendors. Even though the MBF price is equal, one vendor's carload mayrepresent significantly greater marketplace value because it containsthe more desirable lengths of 2×4's, such as market-preferred 16-foot2×4's. When the offering price varies in addition to the mix of lengths,it becomes increasingly difficult to compare quotes from variousvendors. Further, because construction projects often require long leadtimes, the lumber product may need to be priced now, but not delivereduntil a time in the future. Alternately, another species of lumber(i.e., southern pine) may represent an acceptable substitute.

Therefore, from the foregoing, there is a need for a method and systemthat allows buyers to evaluate the price of commodity offeringspossessing varying shipping parameters.

BRIEF SUMMARY

The present disclosure describes a system that operates in a networkedenvironment. The system comprises at least one server that includes anetwork interface, a non-transitory computer-readable medium, and aprocessor in communication with the network interface and thecomputer-readable medium. The computer-readable medium hascomputer-executable instructions stored thereon that, when executed,implement components including at least a metric server adapter and ametrics application. The processor is configured to execute thecomputer-executable instructions stored in the computer-readable medium.

In various embodiments, the metric server adapter includes governinglogic programmed to manage at least one evaluation service and aplurality of predefined instructions that pertain to the evaluationservice and/or data used to provide the at least one evaluation service.The metrics application includes one or more production applications ormodules programmed to manage one or more purchase and/or analysisprocesses, to execute the evaluation service in coordination with themetric server adapter. The metrics application also manages one or moreuser interfaces that, in operation, facilitate interactions with theserver.

In operation, the server is configured to receive a plurality of pricedata sets from at least one computing device in communication with theserver, or retrieve a plurality of price data sets from at least onedata source accessible to the server. Each price data set comprises anoffer to buy or sell that identifies price data for at least one itempossessing a plurality of attributes that include two or more parametervalues or a plurality of items having attributes that differ by at leastone parameter value. At least one price data set represents an unequaloffer in that the price data set identifies at least one item thatdiffers by at least one parameter value from the item as identified inanother price data set.

In response to receipt or retrieval of at least one price data set, theserver implements the evaluation service which causes the metricsapplication, for each price data set, to obtain time-dependent metricdata from at least one data source accessible to the server. Theobtained metric data includes market reference price data for one ormore responsive items possessing attributes that are responsive toattributes of a respective item identified in the price data set. Eachresponsive item in the metric data possesses a plurality of attributesthat include at least one parameter value.

The metrics application evaluates the plurality of attributes of eachresponsive item in the metric data relative to the attributes for therespective item identified in the price data set to dynamically discoverrelationships within the attributes. Discovery of a relationshipcomprising a difference is disclosed to the metric server adapter whichenables the metric server adapter to define offer-specific instructionsfor adapting the metric data for the respective item.

The metrics application normalizes the metric data by executing theoffer-specific instructions for adapting the metric data for therespective item. Execution of at least one offer-specific instructioncauses one or more adjustment values to be generated and applied to themarket reference price data for at least one responsive item thatdiffers by at least one parameter value from the respective item asidentified in the price data set, transforming the market referenceprice data for the at least one responsive item and automaticallyproducing one or more offer-specific market reference price data valuesfor the respective item.

The metrics application generates at least one comparative metric thatpertains to the at least one evaluation service. The comparative metricis based, at least in part, on one or a combination of theoffer-specific market reference price data values produced for therespective item or items identified in a price data set. The comparativemetric comprises a differential ratio or index value that compares theprice data identified for the item or items in the offer with theoffer-specific market reference price data values produced for the itemor items.

Also disclosed herein, in various embodiments, is a method forevaluating unequal offers in a networked environment. The methodincludes receiving, at at least one server, a plurality of price datasets. The server operates under control of computer-executableinstructions that, when executed by a processor, implement componentsincluding at least a governing logic component and a productioncomponent. Each price data set comprises an offer to buy or sell thatidentifies price data for at least one item possessing attributes thatinclude two or more parameter values or a plurality of items havingattributes that differ by at least one parameter value. At least oneprice data set represents an unequal offer in that the price data setidentifies at least one item that differs by at least one parametervalue from the item as identified in another price data set.

For each received price data set, the method further comprisesimplementing, by the server, at least one evaluation service. Inoperation, the evaluation service includes obtaining, by the productioncomponent, time-dependent market-reference data from at least one datasource accessible to the server. The market reference data includesmarket-reference price data for one or more responsive items possessingattributes that are responsive to attributes of a respective itemidentified in the price data set, wherein each responsive item possessesa plurality of attributes including at least one parameter value.

The evaluation service further includes evaluating, by the productioncomponent, the plurality of attributes of each responsive item in themarket reference data relative to the plurality of attributes for therespective item as identified in the price data set to dynamicallydiscover relationships within the attributes. Discovery of arelationship comprising a difference is disclosed to the governing logiccomponent which enables the governing logic component to defineoffer-specific instructions for adapting the market reference data forthe respective item.

The market reference data is normalized, wherein the productioncomponent executes the offer-specific instructions for adapting themarket reference data for the respective item. Execution of at least oneoffer-specific instruction causes one or more adjustment values to begenerated and applied to the market reference price data for at leastone responsive item that differs by at least one parameter value fromthe respective item as identified in the price data set, transformingthe market reference price data for the at least one responsive item andautomatically producing one or more offer-specific market referenceprice data values for the respective item.

At least one comparative metric that pertains to the evaluation serviceis generated by the production component. The comparative metric isbased, at least in part, on one or a combination of the offer-specificmarket reference price data values produced for the respective item oritems identified in the price data set. The comparative metric comprisesa differential ratio or index value that compares the price dataidentified for the item or items in the offer with the offer-specificmarket reference price data values produced for the item or items.

Further disclosed herein is a non-transitory computer-readable mediumhaving computer-executable instructions stored thereon. Thecomputer-executable instructions, when executed, cause at least oneserver in a networked environment to perform operations that includereceiving, at the server, a plurality of price data sets. The serveroperates under control of the computer-executable instructions that,when executed by a processor, implement components including a governinglogic component and a production component.

Each price data set includes price data and represents an offer to buyor sell at least one identified item possessing attributes that includetwo or more parameter values or a plurality of items having attributesthat differ by at least one parameter value. At least one price data setrepresents an unequal offer in that the price data set identifies atleast one item that differs by at least one parameter value from theitem as identified in another price data set.

Implementing at least one evaluation service, for each received pricedata set, the computer-executable instructions cause the server toobtain, by the production component, time-dependent market-referencedata from at least one data source accessible to the server. The marketreference data includes market-reference price data for one or moreresponsive items possessing attributes that are responsive to attributesof a respective item identified in the price data set. Each responsiveitem in the market-reference data possesses a plurality of attributesincluding at least one parameter value.

The production component evaluates the plurality of attributes of eachresponsive item in the market reference data relative to the pluralityof attributes for the respective item as identified in the price dataset to dynamically discover relationships within the attributes.Discovery of a relationship comprising a difference is disclosed to thegoverning logic component which enables the governing logic component todefine offer-specific instructions for adapting the market referencedata for the respective item.

The production component normalizes the market reference data, whereinthe production component executes the offer-specific instructions foradapting the market reference data for the respective item. Execution ofat least one offer-specific instruction causes one or more adjustmentvalues to be generated and applied to the market reference price datafor at least one responsive item that differs by at least one parametervalue from the respective item as identified in the price data set,transforming the market reference price data for the at least oneresponsive item and automatically producing one or more offer-specificmarket reference price data values for the respective item.

The production component generates at least one comparative metric thatpertains to the at least one evaluation service. The comparative metricis based, at least in part, on one or a combination of theoffer-specific market reference price data values produced for therespective item or items identified in the price data set. Thecomparative metric comprises a differential ratio or index value thatcompares the price data identified for the item or items in the offerwith the offer-specific market reference price data values produced forthe item or items.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The foregoing aspects and many of the attendant advantages of thepresent disclosure will become more readily appreciated as the samebecome better understood by reference to the following detaileddescription, when taken in conjunction with the accompanying drawings,wherein:

FIG. 1 is a block diagram of a prior art representative portion of theInternet;

FIG. 2 is a pictorial diagram of a system of devices connected to theInternet, which depict the travel route of data;

FIG. 3 is a block diagram of the several components of the buyer'scomputer shown in FIG. 2 that is used to request information on aparticular route;

FIG. 4 is a block diagram of the several components of an informationserver shown in FIG. 2 that is used to supply information on aparticular route;

FIG. 5 is a flow diagram illustrating the logic of a routine used by theinformation server to receive and process the buyer's actions;

FIGS. 6A-6B are flow diagrams illustrating another embodiment of thelogic used by the information server to receive and process the quotesand quote requests of both buyers and vendors;

FIG. 7 is a flow diagram illustrating another embodiment of the logicused by the information server to execute the process of a catalogpurchase;

FIGS. 8A-8D are images of windows produced by a Web browser applicationinstalled on a client computer accessing a server illustrating oneembodiment of the present disclosure; and

FIG. 9 is a flow diagram illustrating one embodiment of thenormalization process described herein.

DETAILED DESCRIPTION

The term “Internet” refers to the collection of networks and routersthat use the Internet Protocol (IP) to communicate with one another. Arepresentative section of the Internet 100 as known in the prior art isshown in FIG. 1 in which a plurality of local area networks (LANs) 120and a wide area network (WAN) 110 are interconnected by routers 125. Therouters 125 are generally special-purpose computers used to interfaceone LAN or WAN to another. Communication links within the LANs may betwisted wire pair, or coaxial cable, while communication links betweennetworks may utilize 56 Kbps analog telephone lines, or 1 Mbps digitalT-1 lines, and/or 45 Mbps T-3 lines. Further, computers and otherrelated electronic devices can be remotely connected to either the LANs120 or the WAN 110 via a modem and temporary telephone link. Suchcomputers and electronic devices 130 are shown in FIG. 1 as connected toone of the LANs 120 via dotted lines. It will be appreciated that theInternet comprises a vast number of such interconnected networks,computers, and routers and that only a small representative section ofthe Internet 100 is shown in FIG. 1.

The World Wide Web (WWW), on the other hand, is a vast collection ofinterconnected, electronically stored information located on serversconnected throughout the Internet 100. Many companies are now providingservices and access to their content over the Internet 100 using theWWW. In accordance with the present disclosure, and as shown in FIG. 2,there may be a plurality of buyers operating a plurality of clientcomputing devices 235. FIG. 2 generally shows a system 200 of computersand devices to which an information server 230 is connected and to whichthe buyers' computers 235 are also connected. Also connected to theInternet 100 is a plurality of computing devices 250 associated with aplurality of sellers. The system 200 also includes a communicationsprogram, referred to as CEA, which is used on the sellers' computingdevices 250 to create a communication means between the sellers' backendoffice software and the server applications.

The buyers of a market commodity may, through their computers 235,request information about a plurality of items or order over theInternet 100 via a Web browser installed on the buyers' computers.Responsive to such requests, the information server 230, also referredto as a server 230, may combine the first buyer's information withinformation from other buyers on other computing devices 235. The server230 then transmits the combined buyer data to the respective computingdevices 250 associated with the plurality of sellers. Details of thisprocess are described in more detail below in association with FIGS.5-7.

Those of ordinary skill in the art will appreciate that in otherembodiments of the present disclosure, the capabilities of the server230 and/or the client computing devices 235 and 250 may all be embodiedin the other configurations. Consequently, it would be appreciated thatin these embodiments, the server 230 could be located on any computingdevice associated with the buyers' or sellers' computing devices.Additionally, those of ordinary skill in the art will recognize thatwhile only four buyer computing devices 235, four seller computingdevices 250, and one server 230 are depicted in FIG. 2, numerousconfigurations involving a vast number of buyer and seller computingdevices and a plurality of servers 230, equipped with the hardware andsoftware components described below, may be connected to the Internet100.

FIG. 3 depicts several of the key components of the buyer's clientcomputing device 235. As known in the art, client computing devices 235are also referred to as “clients” or “devices,” and client computingdevices 235 also include other devices such as palm computing devices,cellular telephones, or other like forms of electronics. A clientcomputing device can also be the same computing device as the server230. An “agent” can be a person, server, or a client computing device235 having software configured to assist the buyer in making purchasingdecisions based on one or more buyer-determined parameters. Those ofordinary skill in the art will appreciate that the buyer's computer 235in actual practice will include many more components than those shown inFIG. 3. However, it is not necessary that all of these generallyconventional components be shown in order to disclose an illustrativeembodiment for practicing the present invention. As shown in FIG. 3, thebuyer's computer includes a network interface 315 for connecting to theInternet 100. Those of ordinary skill in the art will appreciate thatthe network interface 315 includes the necessary circuitry for such aconnection and is also constructed for use with TCP/IP protocol.

The buyer's computer 235 also includes a processing unit 305, a display310, and a memory 300, all interconnected along with the networkinterface 315 via a bus 360. The memory 300 generally comprises a randomaccess memory (RAM), a read-only memory (ROM), and a permanent massstorage device, such as a disk drive. The memory 300 stores the programcode necessary for requesting and/or depicting a desired route over theInternet 100 in accordance with the present disclosure. Morespecifically, the memory 300 stores a Web browser 330, such asNetscape's NAVIGATOR® or Microsoft's INTERNET EXPLORER® browsers, usedin accordance with the present disclosure for depicting a desired routeover the Internet 100. In addition, memory 300 also stores an operatingsystem 320 and a communications application 325. It will be appreciatedthat these software components may be stored on a computer-readablemedium and loaded into memory 300 of the buyers' computer 235 using adrive mechanism associated with the computer-readable medium, such as afloppy, tape, or CD-ROM drive.

As will be described in more detail below, the user interface whichallows products to be ordered by the buyers are supplied by a remoteserver, i.e., the information server 230 located elsewhere on theInternet, as illustrated in FIG. 2. FIG. 4 depicts several of the keycomponents of the information server 230. Those of ordinary skill in theart will appreciate that the information server 230 includes many morecomponents than shown in FIG. 4. However, it is not necessary that allof these generally conventional components be shown in order to disclosean illustrative embodiment for practicing the present invention. Asshown in FIG. 4, the information server 230 is connected to the Internet100 via a network interface 410. Those of ordinary skill in the art willappreciate that the network interface 410 includes the necessarycircuitry for connecting the information server 230 to the Internet 100,and is constructed for use with TCP/IP protocol.

The information server 230 also includes a processing unit 415, adisplay 440, and a mass memory 450, all interconnected along with thenetwork interface 410 via a bus 460. The mass memory 450 generallycomprises a random access memory (RAM), read-only memory (ROM), and apermanent mass storage device, such as a hard disk drive, tape drive,optical drive, floppy disk drive, or combination thereof. The massmemory 450 stores the program code and data necessary for incident androute analysis as well as supplying the results of that analysis toconsumers in accordance with the present disclosure. More specifically,the mass memory 450 stores a metrics application 425 formed inaccordance with the present disclosure for managing the purchase forumsof commodities products, and a metric server adapter 435 for managingmetric data and the logic for adapting the metric data. In addition, themass memory 450 stores a database 445 of buyer information continuouslylogged by the information server 230 for statistical market analysis. Itwill be appreciated by those of ordinary skill in the art that thedatabase 445 of product and buyer information may also be stored onother servers or storage devices connected to either the informationserver 230 or the Internet 100. Finally, the mass memory 450 stores Webserver software 430 for handling requests for stored informationreceived via the Internet 100 and the WWW, and an operating system 420.It will be appreciated that the aforementioned software components maybe stored on a computer-readable medium and loaded into the mass memory450 of the information server 230 using a drive mechanism associatedwith the computer-readable medium, such as floppy, tape, or CD-ROMdrive. In addition, the data stored in the mass memory 450 and othermemory can be “exposed” to other computers or persons for purposes ofcommunicating data. Thus, “exposing” data from a computing device couldmean transmitting data to another device or person, transferring XMLdata packets, transferring data within the same computer, or other likeforms of data communications.

In accordance with one embodiment of the present disclosure, FIG. 5 is aflow chart illustrating the logic implemented for the creation of aRequest for Quote (RFQ) by a singular buyer or a pool of buyers. Inprocess of FIG. 5, also referred to as the pooling process 500, a buyeror a pool of buyers generate an RFQ which is displayed or transmitted toa plurality of sellers. Responsive to receiving the RFQ, the sellersthen send quotes to the buyers.

In summary, the creation of the RFQ consists of at least one buyerinitially entering general user identification information to initiatethe process. The buyer would then define a Line Item on a Web pagedisplaying an RFQ form. The Line Item is defined per industryspecification and units of product are grouped as a “tally” per industrypractice. The pooling process 500 allows buyers to combine RFQ LineItems with other buyers with like needs. In one embodiment, the pool buyfeature is created by a graphical user interface where the RFQ LineItems from a plurality of buyers are displayed on a Web page to one ofthe pool buyers, referred to as the pool administrator. The server 230also provides a Web-based feature allowing the pool administrator toselectively add each RFQ Line Item to one combined RFQ. The combined RFQis then sent to at least one vendor or seller. This feature provides aforum for pooling the orders of many buyers, which allows individualentities or divisions of larger companies to advantageously bid forlarger orders, thus providing them with more bidding power and thepossibility of gaining a lower price.

The pooling process 500 begins in step 501 where a buyer initiates theprocess by providing buyer purchase data. In step 501, the buyeraccesses a Web page transmitted from the server 230 configured toreceive the buyer purchase data, also referred to as the productspecification data set or the Line Item data. One exemplary Web page forthe logic of step 501 is depicted in FIG. 8A. As shown in FIG. 8A, thebuyer enters the Line Item data specifications in the fields of the Webpage. The Line Item data consists of lumber species and grade 803,number of pieces per unit 804, quantities of the various unitscomprising the preferred assortment in the tally 805A-E, delivery method806, delivery date 807, delivery location 808, and the overall quantity809. In one embodiment, the buyer must define the delivery date aseither contemporaneous “on-or-before” delivery date or specify adelivery date in the future for a “Forward Price” RFQ. In addition, thebuyer selects a metric or multiple metrics in a field 810 per RFQ LineItem (tally). As described in more detail below, the metric providespricing data that is used as a reference point for the buyer to comparethe various quotes returned from the sellers. The buyer RFQ Line Itemdata is then stored in the memory of the server 230.

Returning to FIG. 5, at a next step 503, the server 230 determines ifthe buyer is going to participate in a pool buy. In the process ofdecision block 503, the server 230 provides an option in a Web page thatallows the buyer to post their Line Item data to a vendor or post theirLine Item data to a buyer pool. The window illustrated in FIG. 8A is oneexemplary Web page illustrating these options for a buyer. As shown inFIG. 8A, the links “Post Buyer Pool” 812 and “Post to Vendors” 814 areprovided on the RFQ Web page.

At step 503, if the buyer does not elect to participate in a pool buy,the process continues to step 513 where the server 230 generates arequest for a quote (RFQ) from the buyer's Line Item data. A detaileddescription of how the server 230 generates a request for a quote (RFQ)is summarized below and referred to as the purchase order process 600Adepicted in FIG. 6A.

Alternatively, at decision block 503, if the buyer elects to participatein a pool buy, the process continues to step 505 where the systemnotifies other buyers logged into the server 230 that an RFQ isavailable in a pool, allowing other buyers to add additional Line Items(tallies) to the RFQ. In this part of the process, the Line Items fromeach buyer are received by and stored in the server memory. The LineItems provided by each buyer in the pool are received by the server 230using the same process as described above with reference to block 501and the Web page of FIG. 8A. All of the Line Items stored on the server230 are then displayed to a pool administrator via a Web page or ane-mail message. In one embodiment, the pool administrator is one of thebuyers in a pool where the pool administrator has the capability toselect all of the Line Item data to generate a combined RFQ. The server230 provides the pool administrator with this capability by the use ofany Web-based communicative device, such as e-mail or HTML forms. Aspart of the process, as shown in steps 507 and 509, the pool may be leftopen for a predetermined period of time to allow additional buyers toadd purchase data to the current RFQ.

At decision block 509, the server 230 determines if the pooladministrator has closed the pool. The logic of this step 509 isexecuted when the server 230 receives the combined RFQ data from thepool administrator. The pool administrator can send the combined RFQdata to the server 230 via an HTML form or by other electronic messagingmeans such as e-mail or URL strings. Once the server 230 has determinedthat the pool is closed, the process continues to block 510 where theLine Items from each buyer (the combined RFQ) are sent to all of thebuyers in the pool. The process then continues to step 513 where theserver 230 sends the combined RFQ to the vendors or sellers.

Referring now to FIG. 6A, one embodiment of the purchase-negotiationprocess 600 is disclosed. The purchase-negotiation process 600 is alsoreferred to as a solicited offer process or the market purchase process.In summary, the purchase-negotiation process 600 allows at least onebuyer to submit an RFQ and then view quotes from a plurality of vendorsand purchase items from selected vendor(s). The logic of FIG. 6Aprovides buyers with a forum that automatically manages, collects, andnormalizes the price of desired commodity items. Thepurchase-negotiation process 600 calculates a normalized price data setthat is based on a predefined metric(s). The calculation of thenormalized price data set in combination with the format of the Webpages described herein create an integrated forum where quotes for aplurality of inherently dissimilar products can be easily obtained andcompared.

The purchase-negotiation process 600 begins at step 601 where the RFQ,as generated by one buyer or a pool of buyers in the process depicted inFIG. 5, is sent to a plurality of computing devices 250 associated witha plurality of sellers or vendors. The vendors receive the RFQ via a Webpage transmitted by the server 230. In one embodiment, the vendorsreceive an e-mail message having a hypertext link to the RFQ Web page toprovide notice to the vendor. Responsive to the information in thebuyers' RFQ, the process then continues to step 603 where at least onevendor sends their quote information to the server 230.

In the process of step 603, the vendors respond to the RFQ by sendingtheir price quote to the server 230 for display via a Web page to thebuyer or buyer pool. Generally described, the vendors send an HTML formor an e-mail message with a price and description of the order. Thedescription of the order in the quote message contains the same orderinformation as the RFQ.

FIG. 8B illustrates one exemplary Web page of a vendor quote that isdisplayed to the buyer. As shown in FIG. 8B, the vendor quote includesthe vendor's price 813, the lumber species and grade 803, number ofpieces per unit 804, quantities of the various units comprising thepreferred assortment in the tally 805A-E, delivery method 806, deliverydate 807, and delivery location 808. In the quote response message, thevendor has the capability to modify any of the information that wassubmitted in the RFQ. For example, the vendor may edit the quantityvalues for the various units comprising the preferred assortment in thetally 805A-E. This allows the vendor to adjust the buyer's requestaccording to the vendor's inventory, best means of transportation, etc.All of the vendor's quote information is referred to as price data setor the RFQ Line Item (tally) quote.

Returning to FIG. 6A, the process continues to step 605, where theserver 230 normalizes the price of each RFQ Line Item (tally) quote fromeach vendor. The normalization of the vendor's price is a computationthat evaluates the vendor's price utilizing data from a metric. Thenormalization process is carried out because each vendor may respond tothe Line Items of an RFQ by quoting products that are different from abuyer's RFQ and/or have a different tally configuration. Thenormalization of the metric pricing allows the buyers to objectivelycompare the relative value of the different products offered by theplurality of vendors. For example, one vendor may produce a quote for anRFQ of one unit of 2×4×10, two units of 2×4×12, and three units of2×4×16. At the same time, another vendor may submit a quote for threeunits of 2×4×10, one unit of 2×4×12, and two units of 2×4×16. Eventhough there is some difference between these two offerings, the pricenormalization process provides a means for the buyer to effectivelycompare and evaluate the different quotes even though there arevariations in the products. The price normalization process 900 isdescribed in more detail below in conjunction with the flow diagram ofFIG. 9.

Returning again to FIG. 6A, at step 607 the vendor's quote informationis communicated to the buyer's computer for display. As shown in FIG. 8Band described in detail above, the vendor's quote is displayed via a Webpage that communicates the vendor's quote price 813 and other purchaseinformation. In addition, the vendor's quote page contains a metricprice 815 and a quote price versus metric price ratio 816. The metricprice 815 and the quote price versus metric price ratio 816 are alsoreferred to as a normalized price data value. A ratio higher than one(1) indicates a quote price that is above the metric price, and a lowerratio indicates a quote price that is below the metric price.

Next, at step 609, the buyer or the administrator of the buyer poolcompares the various products and prices quoted by the vendors alongwith the normalized price for each Line Item on the RFQ. In this part ofthe process, the buyer may decide to purchase one of the products from aparticular vendor and sends a notification to the selected vendorindicating the same. The buyer notifies the selected vendor by the useof an electronic means via the server 230, such as an HTML form, a chatwindow, e-mail, etc. For example, the quote Web page depicted in FIG. 8Bshows two different quotes with two different tallies, the first quoteprice 813 of $360, and the second quote price 813A of $320. If the buyerdetermines that they prefer to purchase the materials listed in thefirst quote, the buyer selects the “Buy!” hyperlink 820 or 820Aassociated with the desired tally.

If the buyer is not satisfied with any of the listed vendor quotes, theserver 230 allows the buyer to further negotiate with one or more of thevendors to obtain a new quote. This step is shown in decision block 611,where the buyer makes the determination to either accept a quoted priceor proceed to step 613 where they negotiate with the vendor to obtainanother quote or present a counter-offer. Here, the server 230 providesa graphical user interface configured to allow the buyer and one vendorto electronically communicate, using, e.g., a chat window, streamingvoice communications, or other standard methods of communication. Thereare many forms of electronic communications known in the art that can beused to allow the buyer and vendors to communicate.

The buyer and seller negotiate various quotes and iterate throughseveral steps 603-613 directed by the server 230, where each quote isnormalized, compared, and further negotiated until a quote is acceptedby the buyer or negotiations cease. While the buyer and seller negotiatethe various quotes, the server 230 stores each quote until the twoparties agree on a price. At any step during the negotiation process,the system always presents the buyer with an option to terminate thenegotiation if dissatisfied with the quote(s).

At decision block 611, when a buyer agrees on a quoted price, theprocess then continues to step 615 where the buyer sends a notificationmessage to the vendor indicating they have accepted a quote. Asdescribed above with reference to steps 603-613, the buyer notificationmessage of step 615 may be in the form of a message on a chat window,e-mail, by an HTML form, or the like. However, the buyer notificationmust be transmitted in a format that allows the system to record thetransaction. The buyer notification may include all of the informationregarding the specifications by RFQ Line Item, such as, but not limitedto, the buy price, date, and method of shipment, and payment terms.

The purchase-negotiation process 600 is then finalized when the system,as shown in step 617, sends a confirmation message to a tracking system.The confirmation message includes all of the information related to theagreed sales transaction.

Optionally, the process includes step 619, where the server 230 storesall of the information related to RFQ, offers, and the final salestransaction in a historical database. This would allow the server 230 touse all of the transaction information in an analysis process forproviding an improved method of obtaining a lower market price in futuretransactions and in identifying optimum purchasing strategy. Theanalysis process is described in further detail below. Although theillustrated embodiment is configured to store the data related to thesales transactions, the system can also be configured to store all ofthe iterative quote information exchanged between the buyer and vendor.

Referring now to FIG. 6B, an embodiment of the unsolicited offer process650 is disclosed. In summary, the unsolicited offer process 650, alsoreferred to as the unsolicited market purchase process, allows at leastone buyer to view unsolicited offers from a plurality of vendors andpurchase items from a plurality of vendors from the offers. The logic ofFIG. 6B provides buyers with a forum that automatically manages,collects, and normalizes price quotes based on metric data. By the pricenormalization method of FIG. 6B, the server 230 creates an integratedforum where offers for a plurality of inherently dissimilar products canbe obtained and normalized for determination of a purchase.

The unsolicited offer process 650 begins at step 651 where the pluralityof vendors is able to submit offers to the server 230. This part of theprocess is executed in a manner similar to step 603 of FIG. 6A, wherethe vendor submits a quote to the server 230. However, in the Web pageof step 651, the server 230 generates a Web page containing severaltallies from many different vendors. In addition, at step 651, theserver 230 stores all of the unsolicited offer data provided by thevendors.

Next, at step 653, a buyer views the offers stored on the server 230.This part of the process is carried out in a manner similar to theprocess of step 603 or 607 where the server 230 displays a plurality ofoffers similar to the tallies depicted in FIG. 8A.

Next, at step 655, the buyer selects a metric for the calculation of thenormalized price associated with the selected offer. As described inmore detail below, metric data may come from publicly availableinformation, i.e., price of futures contracts traded on the ChicagoMercantile Exchange, subscription services such as Crowes™ or RandomLengths™ processed via the metric server adapter 435 (shown in FIG. 4),or internally generated metrics derived from the data stored in theserver 230. The normalization calculation, otherwise referred to as thenormalization process, occurs each time the buyer views a differentoffer, and the normalization calculation uses the most current metricdata for each calculation. The normalization process is carried outbecause each vendor will most likely offer products that may vary fromproducts of other vendors and have a different tally configuration fromthose supplied by other vendors. The normalization of the metric pricingallows the buyers to compare the relative value of the differentproducts offered by the number of vendors. The metric price for eachselected offer is displayed in a similar manner as the metric price 815and 816 shown in the Web page of FIG. 8B.

Next, at decision block 657, the buyer selects at least one offer forpurchase. This is similar to the process of FIG. 6A in that the buyerselects the “Buy!” hyperlink 820 associated with the desired tally topurchase an order. The process then continues to steps 659-663, where,at step 659, the process transmits a buy notice to the vendor, then, atstep 661, sends a purchase confirmation to the tracking system, andthen, at step 663, saves the transaction data in the server database.The steps 659-663 are carried out in the same manner as the steps615-619 of FIG. 6A. In the above-described process, the buyernotification may include all of the information regarding thespecifications by RFQ Line Item, and data such as, but not limited to,the buy price, date, and method of shipment, and the payment terms.

Referring now to FIG. 7, a flow diagram illustrating yet anotherembodiment of the present disclosure is shown. FIG. 7 illustrates thecatalog purchase process 700. This embodiment allows buyers to searchfor a catalog price of desired commerce items, enter their purchase databased on the pre-negotiated catalog prices, and to compare those catalogprices with a selected metric price and the current market price,wherein the current market price is determined by thepurchase-negotiation process 600.

The process starts at step 701 where the buyer selects a program buycatalog 443. The program buy catalog 443 provides buyers with thepublished or pre-negotiated price of the desired products. Next, at step703, based on the catalog information, the buyer then enters theirpurchase data. Similar to step 501 of FIG. 5 and the tally shown in FIG.8A, the buyer sends purchase data to the server 230, such as the desiredquantity of each item and the lumber species, grade, etc.

The process then proceeds to decision block 707 where the buyer makes adetermination of whether to purchase the items using the catalog priceor purchase the desired product in the open market. Here, the server 230allows the user to make this determination by displaying the metricprice of each catalog price. This format is similar to the metric price815 and 816 displayed in FIG. 8B.

At decision block 707, if the buyer determines that the catalog price isbetter than a selected metric price, the process then proceeds to steps709, 711, and 713, where a program buy from the catalog is executed, andthe buyer's purchase information is stored on the server 230 and sent tothe vendor's system to confirm the sale. These steps 711-713 are carriedout in the same manner as the confirmation and save steps 617 and 619 asshown in FIG. 6A.

At decision block 707, if the buyer determines that the metric price isbetter than the catalog price, the process continues to step 717 wherethe buyer's purchase data is entered into an RFQ. At this step, theprocess carries out the first five steps 601-609 of the method of FIG.6A to provide buyers with the price data from the open market, as wellas provide the normalized prices for each open market quote. At step719, the server 230 then displays a Web page that allows the user toselect from a purchase option of a catalog or spot (market) purchase. Atdecision block 721, based on the displayed information, the buyer willthen have an opportunity to make a determination of whether they willproceed with a catalog purchase or an open market purchase.

At decision block 721, if the buyer proceeds with the catalog purchase,the process continues to step 709 where the catalog purchase isexecuted. Steps 709-713 used to carry out the catalog purchase are thesame as if the buyer had selected the catalog purchase in step 707.However, if at decision block 721 the buyer selects the option toproceed with the market purchase, the process continues to step 723where the RFQ generated in step 717 is sent to the vendor. Here, theprocess carries out the steps of FIG. 6 to complete the open marketpurchase. More specifically, the process continues to step 609 where thebuyer compares the normalized prices from each vendor. Once a vendor isselected, the negotiation process of steps 603-613 is carried out untilthe buyer decides to execute the purchase. Next, the transaction steps615-619 are carried out to confirm the purchase, notify the trackingsystem, and save the transactional data on the historical database.

Optionally, the process can include a step where the server 230 storesall of the information related to program buy and metric comparisons andthe final sales transaction in a historical database. This would allowthe server 230 to use all of the transaction information in an analysisprocess for providing an improved method of obtaining the value of theprogram. Although the illustrated embodiment is configured to store thedata related to the sales transactions, the system can also beconfigured to store all of the iterative quote information exchangedbetween the buyer and vendor.

The analysis process allows the server 230 to utilize the sales historyrecords stored in steps 619 and 711 to generate price reports forcommunication to various third parties as well as provide a means ofcalculating current market prices for products sold in theabove-described methods. The sales history records are also used as thesource for a metric, such as those used in the process of FIGS. 6A, 6B,and 7. As shown in steps 619, 663, and 711, the server 230 continuallyupdates the historical database for each sales transaction. The analysisreporting process allows a buyer or manager of buyers to conductanalysis on the historical information. This analysis would includemulti-value cross compilation for purposes of determining purchasingstrategies, buyer effectiveness, program performance, vendorperformance, and measuring effectiveness of forward pricing as a riskmanagement strategy.

Referring now to FIG. 9, a flow diagram illustrating the logic of thenormalization process 900 is shown. The logic of the normalizationprocess 900 resides on the server 230 and processes the quotes receivedfrom commodity sellers. The logic begins at step 905 where quote data isobtained from the seller in response to the buyer's RFQ as describedabove.

Next, at step 910, routine 900 iteratively calculates the board footage(BF) of each type of lumber. Once all the totals are calculated for eachtype, routine 900 continues to step 915 where the server 230 calculatesthe total type price.

At step 915, routine 900 iteratively calculates the total type price forthe amount of each type of lumber specified in the quote. This isaccomplished by taking the total board footage (BF) calculated in block910 and multiplying the total BF by the price per MBF specified in thequote. Once all the prices are calculated for each type, routine 900continues to step 920 where the server 230 calculates the total quotedprice. At step 920, the routine 900 calculates the total price for thequote by summing all of the total type prices calculated at step 915.

At step 925, the routine 900 iteratively retrieves the most currentprice for each type of lumber specified in the quote from a predefinedmetric source(s). Metric data may come from publicly availableinformation, i.e., price of futures contracts traded on the ChicagoMercantile Exchange, subscription service publications such as Crowes™or Random Lengths™ processed via the metric server adapter 435 (shown inFIG. 4), or internally generated metrics derived from the serverdatabase. Once all the prices are retrieved for each type, at step 930,the routine 900 then iteratively calculates the market price for thequantity of each type of lumber in the quote. Once the totals for alltypes are calculated, the routine 900 continues to step 935 where theroutine 900 calculates the total market price for the quote by summingall the most current prices calculated in step 930. Although thisexample illustrates that steps 910-920 are executed before steps925-935, these two groups of steps can be executed in any order, or inparallel, so long as they are both executed before a comparison step 940.

At step 940, routine 900 compares the total quoted to the metric priceto arrive at a comparative value. In one exemplary embodiment of thecurrent invention, the comparative value is a “percent of metric” value.A value higher than one hundred (100) percent indicates a price that isabove the metric rate, and a lower percent indicates a price that isbelow the metric rate.

The operation of routine 900 can be further illustrated through anexample utilizing specific exemplary data. In the example, a buyer sendsout a request for a quote (RFQ) requesting a lot of 2×4 S&B lumberconsisting of five units of 2″×4″×8′, two units of 2″×4″×14′, and fiveunits of 2″×4″×16′. The buyer then receives quotes from three sellers.Seller A responds with a tally of six units of 2″×4″×8′, four units of2″×4″×14′, and three units of 2″×4″×16′ for $287 per thousand boardfeet. Seller B responds with a lot of five units of 2″×4″×8′, one unitof 2″×4″×14′, and six units of 2″×4″×16′ for $283 per thousand boardfeet. Seller C responds with a lot of one unit of 2″×4″×8′, five unitsof 2″×4″×14′, and five units of 2″×4″×16′ for $282 per thousand boardfeet. Suppose also that the typical unit size is 294 pieces/unit, andthe metric or reported market price for 2″×4″×8's is $287.50, for2″×4″×14's is $278.50, and for 2″×4″×16′ is $288.

Viewing the MBF prices for the respective quotes is not particularlyinformative, given that certain lengths of lumber are more desirable andpriced accordingly in the marketplace. By processing the quote fromSeller A using routine 900, we arrive at a total MBF of 29.792, giving atotal quoted price of $8,550.30. The selected metric price for the sametypes and quantities of lumber would be $8,471.12; therefore, the quotedprice would have a percent of market value of 100.93%. Processing thequote from Seller B using routine 900, we arrive at a total MBF of29.400, giving a total quoted price of $8,320.20. The selected metricprice for the same types and quantities of lumber, however, would be$8,437.21; therefore, the quoted price would have a percent of marketvalue of 98.61%. Finally, processing the quote from Seller C usingroutine 900, we arrive at a total MBF of 30.968, giving a total quotedprice of $8,732.98. The selected metric price for the same types andquantities of lumber, however, would be $8,767.66; therefore, the quotedprice would have a percent of market value of 99.38%. By looking at thepercent of selected metric value, it is apparent that the price fromSeller B is a better value. As shown in the methods of FIGS. 5-7, thisprice normalization process allows users to compare inherently differentoffers having different quality and quantity values.

In yet another example of an application of the normalization process,additional exemplary data is used to demonstrate the analysis of atransaction having one RFQ from a buyer and two different quotes from aseller, normalized to comparable product of another species. In thisexample, the buyer produces an RFQ listing the following items: onecarload of Eastern SPF (ESPF) lumber having four units of 2″×4″×8′, fourunits of 2″×4″×10′, six units of 2″×4″×12′, two units of 2″×4″×14′, andsix units of 2″×4″×16′. The vendor then responds with two differentquotes with two different unit tallies and two different prices. Thefirst response lists a quote price of $320 per thousand board feet, anda slight modification of the tally provides four units of 2″×4″×8′, fourunits of 2″×4″×10′, six units of 2″×4″×12′, three units of 2″×4″×14′,and five units of 2″×4″×16′. The second response quotes per therequested tally at a price of $322 per thousand board feet. Both quoteslist the delivery location as “Chicago.”

To display the quotes, the server 230 produces a Web page similar tothat displayed in FIG. 8C, where the vendor's modified tally isdisplayed in highlighted text. The buyer can then view a summary metriccomparison or select the hypertext link “View Calculation Detail,” whichthen invokes the server 230 to produce a Web page as shown in FIG. 8D.Referring now to the Web page illustrated in FIG. 8D, the data producedby the server 230 compares the response to a selected metric of adifferent species, Western SPF (WSPF), for items of the same size,grade, and tally. The market price for the same 2×4 tally of ESPF andWSPF are thus simultaneously compared. In an example, Eastern quoted at$322 per thousand board feet, Western metric (Random Lengths™ 6/26/2000print price plus freight of $80/M as defined in Metric Manager) for thesame tally being $331.791. This metric comparison is also represented asQuote/Metric Value or Eastern price representing .970490, or 97% ofcomparable Western product.

In review of the normalization process, the buyer must select a metricsource for price information for a defined item given a set ofattributes, i.e., grade, species, and size. The metric may then bemapped to the RFQ item for comparison and does not have to be theequivalent of the item. For instance, as explained in theabove-described example, it may be desirable to map the marketrelationship of one commodity item to another. The most current pricingdata for the metric is electronically moved from the selected source tothe server 230. As mentioned above, metric data may come from publiclyavailable information, (i.e., price of futures contracts traded on theChicago Mercantile Exchange), or subscription services, (i.e., Crowes™or Random Lengths™ publications), or be an internal metric generated bythe server 230. This metric data is used in the normalization processfor all calculations, as described with reference to the above-describedmethods.

While various embodiments of the invention have been illustrated anddescribed, it will be appreciated that within the scope of the appendedclaims, various changes can be made therein without departing from thespirit of the invention. For example, in an agricultural commodity, anorder for Wheat U.S. #2 HRW could be compared to a selected metric ofWheat U.S. #2 Soft White, similar to how different species are analyzedin the above-described example.

The above system and method can be used to purchase other commodityitems, such as in the trade of livestock. In such a variation, orderinformation such as a lumber tally would be substituted for a meat type,grade, and cut. Other examples of commodity items include agriculturalproducts, metals, or any other items of commerce having several orderparameters.

The invention claimed is:
 1. In a networked environment, a systemcomprising: at least one server that includes: a network interface; anon-transitory computer-readable medium having computer-executableinstructions stored thereon, wherein the computer-executableinstructions, when executed, implement components including at least: ametric server adapter; and a metrics application; and a processor incommunication with the network interface and the computer-readablemedium, wherein the processor is configured to execute thecomputer-executable instructions stored in the computer-readable medium;wherein: the metric server adapter includes governing logic programmedto manage at least one evaluation service and a plurality of predefinedinstructions that pertain to the at least one evaluation service and/ordata used to provide the at least one evaluation service; the metricsapplication includes one or more production applications or modulesprogrammed to manage one or more purchase and/or analysis processes, toexecute the at least one evaluation service in coordination with themetric server adapter, and to manage one or more user interfaces that,in operation, facilitate interactions with the at least one server; andin operation, the at least one server is configured to receive from atleast one computing device in communication with the at least oneserver, or retrieve from at least one data source accessible to the atleast one server, a plurality of price data sets, wherein each pricedata set comprises an offer to buy or sell that identifies price datafor at least one item possessing a plurality of attributes that includetwo or more parameter values or a plurality of items having attributesthat differ by at least one parameter value, and wherein at least oneprice data set represents an unequal offer in that the price data setidentifies at least one item that differs by at least one parametervalue from the item as identified in another price data set; and whereinin response to the receipt or retrieval of at least one price data set,the at least one server implements the at least one evaluation service,which causes the metrics application, for each price data set, to:obtain time-dependent metric data from at least one data sourceaccessible to the at least one server, wherein the obtained metric dataincludes market reference price data for one or more responsive itemspossessing attributes that are responsive to attributes of a respectiveitem identified in the price data set, wherein each responsive item inthe metric data possesses a plurality of attributes that include atleast one parameter value; evaluate the plurality of attributes of eachresponsive item in the metric data relative to the attributes for therespective item identified in the price data set to dynamically discoverrelationships within the attributes, wherein discovery of a relationshipcomprising a difference is disclosed to the metric server adapter whichenables the metric server adapter to define offer-specific instructionsfor adapting the metric data for the respective item; normalize themetric data by executing the offer-specific instructions for adaptingthe metric data for the respective item, wherein execution of at leastone offer-specific instruction causes one or more adjustment values tobe generated and applied to the market reference price data for at leastone responsive item that differs by at least one parameter value fromthe respective item as identified in the price data set, transformingthe market reference price data for the at least one responsive item andautomatically producing one or more offer-specific market referenceprice data values for the respective item; and generate at least onecomparative metric that pertains to the at least one evaluation service,wherein the comparative metric is based, at least in part, on one or acombination of the offer-specific market reference price data valuesproduced for the respective item or items identified in a price dataset, the at least one comparative metric comprising a differential ratioor index value that compares the price data identified for the item oritems in the offer with the offer-specific market reference price datavalues produced for the item or items.
 2. The system of claim 1, whereinat least one of the plurality of received or retrieved price data setsidentifies an item that is not a perfect substitute for the item asidentified in another received or retrieved price data set, wherein theitem is an alternate or substitute item with attributes that differ byone or more parameter values from the item as identified in anotherreceived or retrieved price data set.
 3. The system of claim 1, whereinthe differential ratio or index value is a measure of offer price inrelation to market value that reduces the complexity of comparingunequal offers, wherein an offer-to-sell with a lowest differentialratio or index value represents an optimal opportunity to buy therespective item or items, and wherein an offer-to-buy with a highestdifferential ratio or index value represents an optimal opportunity tosell the respective item or items.
 4. The system of claim 3, wherein atleast one offer that is an offer-to-buy is compared to at least oneoffer that is an offer-to-sell.
 5. The system of claim 1, whereinimplementation of the at least one evaluation service and/or executionof at least one predefined instruction that pertains to the at least oneevaluation service causes the metrics application to compare two or moreof the received or retrieved price data sets, including at least oneunequal offer, using at least one comparative metric generated for eachprice data set, wherein a result of the comparison is exposed to one ormore computing devices in communication with the at least one server. 6.The system of claim 5, wherein selection by the user-agent of apredefined link that was pre-associated with at least one price data setidentified in the exposed comparison causes the metrics application toautomatically transmit, on behalf of the user-agent, at least one buy orsell notice for the at least one item associated with the link, via thenetwork interface, to the computing device from which the price data setwas received.
 7. The system of claim 1, wherein the metrics applicationalgorithmically processes the attributes to dynamically identify atleast one relationship comprising a difference, wherein the identifiedrelationship comprising a difference can include a new or previouslyunknown relationship, and wherein coordinated operation of the metricsapplication and the metric server adapter enables the metricsapplication to produce the one or more offer-specific market referenceprice data values for the respective item as identified in the pricedata set without relying on a predefined model having predefinedrelations that remain fixed within the model.
 8. The system of claim 1,wherein the metric server adapter algorithmically processes theplurality of predefined instructions, the plurality of attributes andparameter values identified for the respective item, and the at leastone discovered relationship comprising a difference, to ascertain whichof the plurality of predefined instructions are applicable to theresponsive item in order to contextually align the responsive item withthe respective item, wherein the offer-specific instructions defined bythe metric server adapter represent an evolved set of instructions thatcomprise more than a filtered subset of the predefined instructions. 9.The system of claim 1, wherein the predefined instructions that pertainto the at least one evaluation service include one or moreindustry-specific instructions or one or more instructions predefinedfor at least one particular user-agent, wherein the coordinatedoperation of the metrics application and the metric server adapterenables the at least one server to provide an evaluation service that iscustomized for the particular user-agent or the specific industrywithout custom-coding the computer-executable instructions.
 10. Thesystem of claim 1, wherein the predefined instructions that pertain tothe at least one evaluation service were not predefined for, orpre-mapped to, a particular price data set.
 11. The system of claim 1,wherein the metric server adapter is programmed to coordinate aconditional execution, by the metrics application, of the offer-specificinstructions for adapting the metric data for the respective item. 12.The system of claim 11, wherein a conditional execution of theoffer-specific instructions is expressed as “IF condition THEN action,”or is priority weighted, recursive, or subject to another method ofcontrol defined by the metric server adapter.
 13. The system of claim11, wherein one or more offer-specific instructions for adapting themetric data for the respective item specify validation rules and/orpredefined statistical criteria to be satisfied, and wherein aconditional execution of the offer-specific instructions causes themetrics application to produce the one or more offer-specific marketreference price data values for the respective item when after theadjustment values resulting from the offer-specific instructions havebeen applied and the specified validation rules and/or predefinedstatistical criteria have been satisfied.
 14. The system of claim 1,wherein the one or more identified parameter values include at least oneof a grade, a rating measure, a species, an item type, a brand, a size,a unit of measure, a tally, a shipping or receiving location, a methodof delivery, a delivery date, a time of service, a warranty, a paymentterm, or a transaction type.
 15. The system of claim 14, wherein thedelivery date or time of service specifies one or more fulfillment datesin the future, and comprises a forward price transaction type.
 16. Thesystem of claim 14, wherein delivery comprises a financial delivery. 17.The system of claim 14, wherein delivery comprises an exchange of atleast one item for at least one other item, and wherein the at least oneother item differs by at least one parameter value from the at least oneitem.
 18. The system of claim 1, wherein the time-dependent metric dataincludes metric data for one or more responsive items from a time orperiod of time that corresponds with the time or period of time of therespective item in the price data set, a predefined time, or acontinuously sliding interval of time that represents a most currentperiod of time.
 19. The system of claim 1, wherein implementation of theat least one evaluation service and/or execution of at least onepredefined instruction that pertains to the at least one evaluationservice causes the metrics application to convert data defined by aunit-of-measure into standardized or common units of measure beforeproducing the one or more offer-specific market reference price datavalues for the at least one item as identified in each price data setusing data possessing consistent units of measure, wherein thetransformation of the market reference price data for the at least oneresponsive item occurs independent of the unit-of-measure conversion ofthe data.
 20. The system of claim 1, wherein implementation of the atleast one evaluation service and/or execution of at least one predefinedinstruction that pertains to the at least one evaluation service causesthe metrics application to obtain only metric data resulting from acomputer-based interaction and/or to use only electronically-createdmetric data to produce the one or more offer-specific market referenceprice data values for the respective item, wherein theelectronically-created metric data includes data comprising a timestampthat identifies a particular time or period of time and does not includehuman-reported transaction data or transaction data that was manuallytranscribed into a digital format.
 21. In a networked environment, amethod for evaluating unequal offers comprising: receiving, at at leastone server, a plurality of price data sets, wherein the at least oneserver is operating under control of computer-executable instructionsthat, when executed by a processor, implement components including atleast a governing logic component and a production component, whereineach price data set comprises an offer to buy or sell that identifiesprice data for at least one item possessing attributes that include twoor more parameter values or a plurality of items having attributes thatdiffer by at least one parameter value, wherein at least one price dataset represents an unequal offer in that the price data set identifies atleast one item that differs by at least one parameter value from theitem as identified in another price data set; and wherein, for eachreceived price data set, the method further comprises implementing, bythe at least one server, at least one evaluation service that, inoperation, includes: obtaining, by the production component,time-dependent market-reference data from at least one data sourceaccessible to the at least one server, wherein the market reference dataincludes market-reference price data for one or more responsive itemspossessing attributes that are responsive to attributes of a respectiveitem identified in the price data set, wherein each responsive itempossesses a plurality of attributes including at least one parametervalue; evaluating, by the production component, the plurality ofattributes of each responsive item in the market reference data relativeto the plurality of attributes for the respective item as identified inthe price data set to dynamically discover relationships within theattributes, wherein discovery of a relationship comprising a differenceis disclosed to the governing logic component which enables thegoverning logic component to define offer-specific instructions foradapting the market reference data for the respective item; andnormalizing the market reference data, wherein the production componentexecutes the offer-specific instructions for adapting the marketreference data for the respective item, wherein execution of at leastone offer-specific instruction causes one or more adjustment values tobe generated and applied to the market reference price data for at leastone responsive item that differs by at least one parameter value fromthe respective item as identified in the price data set, transformingthe market reference price data for the at least one responsive item andautomatically producing one or more offer-specific market referenceprice data values for the respective item; and generating, by theproduction component, at least one comparative metric that pertains tothe at least one evaluation service, wherein the comparative metric isbased, at least in part, on one or a combination of the offer-specificmarket reference price data values produced for the respective item oritems identified in the price data set, the comparative metriccomprising a differential ratio or index value that compares the pricedata identified for the item or items in the offer with theoffer-specific market reference price data values produced for the itemor items.
 22. The method of claim 21, wherein implementation of the atleast one evaluation service and/or execution of at least one predefinedinstruction that pertains to the at least one evaluation service causesthe production component to compare at least a subset of the receivedprice data sets, including at least one unequal offer, using at leastone comparative metric generated for each price data set, wherein aresult of the comparison is exposed to one or more computing devices incommunication with the at least one server.
 23. The method of claim 21,wherein the differential ratio or index value is a measure of offerprice in relation to market value that reduces the complexity ofcomparing unequal offers, wherein an offer-to-sell with a lowestdifferential ratio or index value represents an optimal opportunity tobuy the respective item or items, and wherein an offer-to-buy with ahighest differential ratio or index value represents an optimalopportunity to sell the respective item or items.
 24. The method ofclaim 21, wherein the governing logic component includes one or moregoverning logic applications or modules programmed to manage the atleast one evaluation service and a plurality of predefined instructionsthat pertain to the at least one evaluation service and/or data used toprovide the at least one evaluation service.
 25. The method of claim 24,further comprising, by the governing logic component, algorithmicallyprocessing the plurality of predefined instructions that pertain to theat least one evaluation service, the plurality of attributes andparameter values identified for the respective item, and the at leastone discovered relationship comprising a difference, to ascertain whichof the plurality of predefined instructions are applicable to theresponsive item in order to contextually align the responsive item withthe respective item, wherein the offer-specific instructions defined bythe governing logic component represent an evolved set of instructionsthat comprise more than a filtered subset of the predefinedinstructions.
 26. The method of claim 24, wherein the predefinedinstructions that pertain to the at least one evaluation service includeone or more industry-specific instructions or one or more instructionspredefined for at least one particular user-agent, wherein thecoordinated operation of the production component and the governinglogic component enables the at least one server to provide an evaluationservice that is customized for the particular user-agent or the specificindustry without custom-coding the computer-executable instructions thatcomprise the production component.
 27. The method of claim 26, whereinat least one predefined instruction that pertains to the at least oneevaluation service and a particular user-agent or a specific industry,when executed, causes the production component to obtain metric datathat is responsive to an alternate item, wherein the alternate item is asubstitute item or an item possessing attribute data that differs by atleast one parameter value from the respective item as identified in theprice data set.
 28. The method of claim 21, wherein the productioncomponent includes one or more applications or modules programmed tomanage one or more purchase and/or analysis processes, to execute the atleast one evaluation service in coordination with the governing logiccomponent, and manage one or more user interfaces that, in operation,facilitate interactions with the at least one server.
 29. The method ofclaim 21, wherein the production component algorithmically processes theattributes to dynamically identify at least one relationship comprisinga difference, wherein the identified relationship comprising adifference can include a new or previously unknown relationship, andwherein coordinated operation of the production component and thegoverning logic component enables the metrics application to produce theone or more offer-specific market reference price data values for therespective item as identified in the price data set without relying on apredefined model having predefined relations that remain fixed withinthe model.
 30. The method of claim 21, wherein the production componentmanages at least one user interface that, in operation, facilitates datacommunication in XML format, enabling the production component todynamically change, dynamically route, and/or pre-configure the data formovement of the data in an integrated data exchange with anothercomputing device in communication with the at least one server.
 31. Themethod of claim 21, wherein the governing logic component coordinates aconditional execution, by the production component, of theoffer-specific instructions for adapting the metric data for therespective item.
 32. The method of claim 31, wherein a conditionalexecution of the offer-specific instructions is expressed as “IFcondition THEN action,” or is priority weighted, recursive, or issubject to another method of control defined by the governing logiccomponent.
 33. The method of claim 31, wherein one or moreoffer-specific instructions for adapting the metric data for therespective item specify validation rules and/or predefined statisticalcriteria to be satisfied, and wherein a conditional execution of theoffer-specific instructions causes the production component to producethe one or more offer-specific market reference price data values forthe respective item after the adjustment values resulting from theoffer-specific instructions have been applied and the specifiedvalidation rules and/or predefined statistical criteria have beensatisfied.
 34. The method of claim 21, wherein the one or moreidentified parameter values include at least one of a grade, a ratingmeasure, a species, an item type, a brand, a size, a unit of measure, atally, a shipping or receiving location, a method of delivery, adelivery date, a time of service, a warranty, a payment term, or atransaction type.
 35. The method of claim 34, wherein the delivery dateor time of service specifies one or more fulfillment dates in thefuture, and comprises a forward price transaction type.
 36. The methodof claim 21, wherein implementation of the at least one evaluationservice and/or execution of at least one predefined instruction thatpertains to the at least one evaluation service causes the productioncomponent to convert data defined by a unit-of-measure into standardizedor common units of measure before producing the one or moreoffer-specific market reference price data values for the at least onerespective item, wherein the transformation of the market referenceprice data for the at least one responsive item occurs independent ofthe unit-of-measure conversion of the data.
 37. The method of claim 21,wherein implementation of the at least one evaluation service and/orexecution of at least one predefined instruction that pertains to the atleast one evaluation service causes the production component to obtainonly market-reference data resulting from a computer-based interactionand/or to use only electronically-created market-reference data toproduce the one or more offer-specific market reference price datavalues for the respective item, wherein the electronically-createdmarket-reference data includes data comprising a timestamp thatidentifies a particular time or period of time and does not includehuman-reported transaction data or transaction data that was manuallytranscribed into a digital format.
 38. The method of claim 21, whereinthe at least one item identified in the price data set represents aspecific version or particular form of a physical product or rawmaterial, an intangible product, a service, or a combination thereof.39. In a networked environment, a non-transitory computer-readablemedium having computer-executable instructions stored thereon, whereinthe computer-executable instructions, when executed, cause at least oneserver to perform operations comprising: receiving, at the at least oneserver, a plurality of price data sets, wherein the at least one serveris operating under control of computer-executable instructions that,when executed by a processor, implement components including a governinglogic component and a production component, wherein each price data setincludes price data and represents an offer to buy or sell at least oneidentified item possessing attributes that include two or more parametervalues or a plurality of items having attributes that differ by at leastone parameter value, and wherein at least one price data set representsan unequal offer in that the price data set identifies at least one itemthat differs by at least one parameter value from the item as identifiedin another price data set; and implementing at least one evaluationservice wherein, for each received price data set, thecomputer-executable instructions cause the at least one server to:obtain, by the production component, time-dependent market-referencedata from at least one data source accessible to the at least oneserver, wherein the market reference data includes market-referenceprice data for one or more responsive items possessing attributes thatare responsive to attributes of a respective item identified in theprice data set, wherein each responsive item in the market-referencedata possesses a plurality of attributes including at least oneparameter value; evaluate, by the production component, the plurality ofattributes of each responsive item in the market reference data relativeto the plurality of attributes for the respective item as identified inthe price data set to dynamically discover relationships within theattributes, wherein discovery of a relationship comprising a differenceis disclosed to the governing logic component which enables thegoverning logic component to define offer-specific instructions foradapting the market reference data for the respective item; normalizethe market reference data, wherein the production component executes theoffer-specific instructions for adapting the market reference data forthe respective item, wherein execution of at least one offer-specificinstruction causes one or more adjustment values to be generated andapplied to the market reference price data for at least one responsiveitem that differs by at least one parameter value from the respectiveitem as identified in the price data set, transforming the marketreference price data for the at least one responsive item andautomatically producing one or more offer-specific market referenceprice data values for the respective item; and generate, by theproduction component, at least one comparative metric that pertains tothe at least one evaluation service, wherein the comparative metric isbased, at least in part, on one or a combination of the offer-specificmarket reference price data values produced for the respective item oritems identified in the price data set, the comparative metriccomprising a differential ratio or index value that compares the pricedata identified for the item or items in the offer with theoffer-specific market reference price data values produced for the itemor items.
 40. The computer-readable medium of claim 39, wherein thecomputer-executable instructions cause the governing logic component,including one or more governing logic applications or modules, to managethe at least one evaluation service and a plurality of predefinedinstructions that pertain to the at least one evaluation service and/ordata used to provide the at least one evaluation service.
 41. Thecomputer-readable medium of claim 40, wherein the computer-executableinstructions cause the governing logic component to algorithmicallyprocess the plurality of predefined instructions, the plurality ofattributes and parameter values identified for the respective item, andthe at least one discovered relationship comprising a difference, toascertain which of the plurality of predefined instructions areapplicable to the responsive item in order to contextually align theresponsive item with the respective item, wherein the offer-specificinstructions defined by the governing logic component represent anevolved set of instructions that comprise more than a filtered subset ofthe predefined instructions.
 42. The computer-readable medium of claim39, wherein the computer-executable instructions cause the productioncomponent to manage one or more purchase and/or analysis processes, toexecute the at least one evaluation service in coordination with thegoverning logic component, and manage one or more user interfaces that,in operation, facilitate interactions with the at least one server. 43.The computer-readable medium of claim 42, wherein thecomputer-executable instructions cause the production component toalgorithmically processes the attributes to dynamically identify atleast one relationship comprising a difference, wherein the identifiedrelationship comprising a difference can include a new or previouslyunknown relationship, and wherein coordinated operation of theproduction component and the governing logic component enables themetrics application to produce the one or more offer-specific marketreference price data values for the respective item as identified in theprice data set without relying on a predefined model having predefinedrelations that remain fixed within the model.
 44. The computer-readablemedium of claim 39, wherein the computer-executable instructions causethe production component to compare at least a subset of the receivedprice data sets, including at least one unequal offer, using at least acomparative metric generated for each price data set, wherein a resultof the comparison is exposed to one or more computing devices incommunication with the at least one server.
 45. The computer-readablemedium of claim 39, wherein the computer-executable instructions causethe production component to generate a differential ratio or index valuethat is a measure of offer price in relation to market value thatreduces the complexity of comparing unequal offers, wherein anoffer-to-sell with a lowest differential ratio or index value representsan optimal opportunity to buy the respective item or items, and whereinan offer-to-buy with a highest differential ratio or index valuerepresents an optimal opportunity to sell the respective item or items.